Real-time video deblurring
    1.
    发明授权
    Real-time video deblurring 失效
    实时视频脱模

    公开(公告)号:US08611690B2

    公开(公告)日:2013-12-17

    申请号:US13387333

    申请日:2009-10-21

    IPC分类号: G06K9/40 G09G5/00 H04N1/407

    摘要: A method of reducing blurring in an image of size greater than M columns by N rows of pixels, comprises deriving a blur kernel k representing the blur in the image, and deriving an inverse blur kernel k−1. The inverse blur kernel is given by (I) where h(m) is the sum of the first m terms of the series (II) δ is the Dirac delta, m is greater than 1, and h(m) is a two dimensional matrix of size M×N. The two dimensional matrix h(m) is convolved with the image over the whole image in the image pixel domain to produce an image with reduced blur. The method may be applied to a video sequence allowing the sequence of images to be deblurred in real time.

    摘要翻译: 减少尺寸大于M列乘以N行像素的图像中的模糊的方法包括导出表示图像中的模糊的模糊核k,并导出反模糊核k-1。 逆模糊核由(I)给出,其中h(m)是系列的第一个m项的和(II),δ是狄拉克delta,m大于1,h(m)是二维的 矩阵为M×N。 二维矩阵h(m)与图像像素域中的整个图像一起卷积,以产生模糊减少的图像。 该方法可以应用于允许实时地去除图像序列的视频序列。

    REAL-TIME VIDEO DEBLURRING
    2.
    发明申请
    REAL-TIME VIDEO DEBLURRING 失效
    实时视频脱机

    公开(公告)号:US20120155785A1

    公开(公告)日:2012-06-21

    申请号:US13387333

    申请日:2009-10-21

    IPC分类号: G06K9/40

    摘要: A method of reducing blurring in an image of size greater than M columns by N rows of pixels, comprises deriving a blur kernel k representing the blur in the image, and deriving an inverse blur kernel k−1. The inverse blur kernel is given by (I) where h(m) is the sum of the first m terms of the series (II) δ is the Dirac delta, m is greater than 1, and h(m) is a two dimensional matrix of size M×N. The two dimensional matrix h(m) is convolved with the image over the whole image in the image pixel domain to produce an image with reduced blur. The method may be applied to a video sequence allowing the sequence of images to be deblurred in real time.

    摘要翻译: 减少尺寸大于M列乘以N行像素的图像中的模糊的方法包括导出表示图像中的模糊的模糊核k,并导出反模糊核k-1。 逆模糊核由(I)给出,其中h(m)是系列的第一个m项的和(II),δ是狄拉克delta,m大于1,h(m)是二维的 矩阵为M×N。 二维矩阵h(m)与图像像素域中的整个图像一起卷积,以产生模糊减少的图像。 该方法可以应用于允许实时地去除图像序列的视频序列。

    IMAGE DEFECT DETECTION
    6.
    发明申请
    IMAGE DEFECT DETECTION 有权
    图像缺陷检测

    公开(公告)号:US20110069894A1

    公开(公告)日:2011-03-24

    申请号:US12566334

    申请日:2009-09-24

    IPC分类号: G06K9/68

    CPC分类号: G06K9/036

    摘要: Disclosed is a computer implemented method of detecting a defect in a printed image, the method comprising the steps of: receiving a target image comprising digital image data representing a scan of the printed image; receiving a reference image comprising digital image data representing a reference of the printed image; calculating a structural dissimilarity measure, D, associated with a target pixel located in the target image and a reference pixel located in the reference image; and, determining on the basis of the structural dissimilarity measure whether a defect is present at the target pixel, wherein the structural dissimilarity measure is calculated using a structural measure, s, and a contrast measure, c; the structural measure calculated using a spatial cross-correlation associated with a target region, {right arrow over (x)}, containing the target pixel and a reference region, {right arrow over (y)}, containing the reference pixel, and the contrast measure calculated using a standard deviation associated with the target region, and a standard deviation associated with the reference region.

    摘要翻译: 公开了一种检测打印图像缺陷的计算机实现方法,该方法包括以下步骤:接收包括表示打印图像的扫描的数字图像数据的目标图像; 接收包括表示所述打印图像的参考的数字图像数据的参考图像; 计算与位于所述目标图像中的目标像素和位于所述参考图像中的参考像素相关联的结构不相似度量D; 并且,基于结构不相似性来确定在目标像素处是否存在缺陷,其中使用结构测量和对比度测量来计算结构不相似性度量,c; 使用与目标区域相关联的空间互相关的结构测量值(包含目标像素的右箭头(x)}),以及包含参考像素的参考区域{右箭头(y)}),以及 使用与目标区域相关联的标准偏差计算的对比度测量,以及与参考区域相关联的标准偏差。

    Image defect detection
    7.
    发明授权
    Image defect detection 有权
    图像缺陷检测

    公开(公告)号:US08326079B2

    公开(公告)日:2012-12-04

    申请号:US12566334

    申请日:2009-09-24

    IPC分类号: G06K9/00

    CPC分类号: G06K9/036

    摘要: Disclosed is a computer implemented method of detecting a defect in a printed image, the method comprising the steps of: receiving a target image comprising digital image data representing a scan of the printed image; receiving a reference image comprising digital image data representing a reference of the printed image; calculating a structural dissimilarity measure, D, associated with a target pixel located in the target image and a reference pixel located in the reference image; and, determining on the basis of the structural dissimilarity measure whether a defect is present at the target pixel, wherein the structural dissimilarity measure is calculated using a structural measure, s, and a contrast measure, c; the structural measure calculated using a spatial cross-correlation associated with a target region, {right arrow over (x)}, containing the target pixel and a reference region, {right arrow over (y)}, containing the reference pixel, and the contrast measure calculated using a standard deviation associated with the target region, and a standard deviation associated with the reference region.

    摘要翻译: 公开了一种检测打印图像缺陷的计算机实现方法,该方法包括以下步骤:接收包括表示打印图像的扫描的数字图像数据的目标图像; 接收包括表示所述打印图像的参考的数字图像数据的参考图像; 计算与位于所述目标图像中的目标像素和位于所述参考图像中的参考像素相关联的结构不相似度量D; 并且,基于结构不相似性来确定在目标像素处是否存在缺陷,其中使用结构测量和对比度测量来计算结构不相似性度量,c; 使用与目标区域相关联的空间互相关的结构测量值(包含目标像素的右箭头(x)}),以及包含参考像素的参考区域{右箭头(y)}),以及 使用与目标区域相关联的标准偏差计算的对比度测量,以及与参考区域相关联的标准偏差。

    Multiclass classification of points
    9.
    发明授权
    Multiclass classification of points 有权
    积分多类分类

    公开(公告)号:US08924316B2

    公开(公告)日:2014-12-30

    申请号:US13563690

    申请日:2012-07-31

    IPC分类号: G06F15/18 G06T3/40 G06K9/62

    CPC分类号: G06T3/40 G06K9/6287

    摘要: A method includes obtaining, by executing a module stored on a non-transitory computer-readable storage device, approximately-zero polynomials for each of multiple classes. The method further includes evaluating the approximately-zero polynomials for each class on a plurality of points to compute distances from each point to each of the classes. The method also includes scaling the approximately-zero polynomials based on the distances and classifying the points based on the scaled approximately-zero polynomials.

    摘要翻译: 一种方法包括通过执行存储在非暂时计算机可读存储设备上的模块来获得针对多个类别中的每一个的近似零多项式。 该方法还包括评估多个点上的每个类的近似零多项式以计算从每个点到每个类的距离。 该方法还包括基于距离缩放近似零多项式并基于缩放的近似零多项式对点进行分类。

    Mapping tasks to execution threads
    10.
    发明授权
    Mapping tasks to execution threads 有权
    将任务映射到执行线程

    公开(公告)号:US08887160B2

    公开(公告)日:2014-11-11

    申请号:US13301301

    申请日:2011-11-21

    IPC分类号: G06F9/46 G06F9/50

    CPC分类号: G06F9/5027 G06F2209/503

    摘要: Tasks are mapped to execution threads of a parallel processing device. Tasks are mapped from the list of tasks to execution threads of the parallel processing device that are free. The parallel processing device is allowed to perform the tasks mapped to the execution threads of the parallel processing device for a predetermined number of execution cycles. When the parallel processing device has performed the tasks mapped to the execution threads of the parallel processing device for the predetermined number of execution cycles, the parallel processing device is suspended from further performing the tasks to allow the parallel processing device to determine which execution threads have completed performance of mapped tasks and are therefore free.

    摘要翻译: 任务映射到并行处理设备的执行线程。 任务从任务列表映射到并行处理设备的空闲执行线程。 允许并行处理设备执行映射到并行处理设备的执行线程的任务达预定数量的执行周期。 当并行处理装置在预定数量的执行周期中执行映射到并行处理装置的执行线程的任务时,暂停并行处理装置进一步执行任务以允许并行处理装置确定哪个执行线程具有 完成映射任务的性能,因此是免费的。